testZeroes | R Documentation |

Test for differential proportions of zero expression between two conditions
for a specified set of genes; adapted from the R/Bioconductor package `scDD`

by Korthauer et al. (2016)

```
testZeroes(x, y, these = seq_len(nrow(x)))
## S4 method for signature 'matrix,vector,ANY'
testZeroes(x, y, these = seq_len(nrow(x)))
## S4 method for signature 'SingleCellExperiment,SingleCellExperiment,vector'
testZeroes(x, y, these = seq_len(nrow(x)))
```

`x` |
matrix of single-cell RNA-sequencing expression data with genes in
rows and cells (samples) in columns [alternatively, a |

`y` |
vector of condition labels [alternatively, a |

`these` |
vector of row numbers (i.e. gene numbers) employed to test for differential proportions of zero expression; default is seq_len(nrow(dat)) |

Test for differential proportions of zero gene expression between two
conditions using a logistic regression model accounting for the cellular detection rate. Adapted from the R/Bioconductor package `scDD`

by Korthauer et al. (2016).

In the test, the null hypothesis that there are no differential proportions of zero gene expression (DPZ) is tested against the alternative that there are DPZ.

A vector of (unadjusted) p-values

Korthauer, K. D., Chu, L.-F., Newton, M. A., Li, Y., Thomson, J., Stewart, R., and Kendziorski, C. (2016). A statistical approach for identifying differential distributions in single-cell RNA-seq experiments. Genome Biology, 17:222.

```
#simulate scRNA-seq data
set.seed(24)
nb.sim1<-rnbinom(n=(750*250),1,0.7)
dat1<-matrix(data=nb.sim1,nrow=750,ncol=250)
nb.sim2a<-rnbinom(n=(250*100),1,0.7)
dat2a<-matrix(data=nb.sim2a,nrow=250,ncol=100)
nb.sim2b<-rnbinom(n=(250*150),5,0.2)
dat2b<-matrix(data=nb.sim2b,nrow=250,ncol=150)
dat2<-cbind(dat2a,dat2b)
dat<-rbind(dat1,dat2)*0.25
#randomly shuffle the rows of the matrix to create the input matrix
set.seed(32)
dat<-dat[sample(nrow(dat)),]
condition<-c(rep("A",100),rep("B",150))
#call testZeroes with a matrix and a vector including conditions
#test for differential proportions of zero expression over all rows (genes)
testZeroes(dat, condition)
#test for differential proportions of zero expression only for the second row (gene)
testZeroes(dat, condition, these=2)
#alternatively, call testZeroes with two SingleCellExperiment objects
#note that the possibly pre-processed and normalized expression matrices need to be
#included using the "counts" argument
sce.A <- SingleCellExperiment::SingleCellExperiment(
assays=list(counts=dat[,1:100]))
sce.B <- SingleCellExperiment::SingleCellExperiment(
assays=list(counts=dat[,101:250]))
#test for differential proportions of zero expression over all rows (genes)
testZeroes(sce.A,sce.B,these=seq_len(nrow(sce.A)))
#test for differential proportions of zero expression only for the second row (gene)
testZeroes(sce.A,sce.B,these=2)
```

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